Use this checklist before you launch a SaaS app built with AI coding tools. It covers the production risks GoForLaunch sees most often in Lovable, Bolt, Cursor, v0, Supabase, Stripe and Next.js projects.
A vibe-coded app is not unsafe because AI helped build it. It becomes unsafe when demo-friendly code reaches production without server-side authorization, tenant isolation, secret handling, payment verification and operational controls. The checklist below turns those risks into a launch review.
AI-generated apps often hide admin buttons in React while leaving the API route open. Every sensitive read, write and billing action should verify the user and workspace on the server.
Row Level Security should be enabled on tenant data tables, with policies scoped to the authenticated user or organization. A missing policy is one of the fastest ways to leak customer data.
Look for Stripe live keys, Supabase service role keys, OpenAI keys, GitHub tokens, JWT secrets and webhook secrets. Public environment variables should never contain privileged credentials.
A Stripe route should read the raw request body, verify the signature, reject replayed or duplicate events and resolve the purchased plan from Stripe line items instead of trusting metadata.
Any route shaped like /api/projects/[id], /api/invoices/[id] or /api/files/[id] should query by both the requested ID and the authenticated user or organization.
Generation, scan, upload and auth routes can become expensive quickly. Apply per-IP and per-account limits, then return a clear 429 when the limit is reached.
Do not pair wildcard origins with credentials. For SSRF-prone features such as webhooks, runtime scans or URL imports, block private IP ranges and cloud metadata addresses.
Forms generated by AI tools often trust the frontend. Validate request payloads with a shared schema and reject unexpected fields before writing to the database.
Add security headers, robots.txt, sitemap.xml, canonical metadata, a status page, privacy/security pages and an incident contact before a public launch.
GoForLaunch maps scanner findings to business risk: tenant data exposure, revenue risk, trust damage and launch blockers. The output is written for founders but detailed enough for engineers to review.
47 security and launch-readiness checks tuned for AI-codegen patterns
Severity-ranked findings with code snippets and file paths
Supabase RLS, Stripe, Auth.js, CORS, SSRF, IDOR and secrets coverage
One-time scan, free beta access, API, CLI and GitHub Action options
It is a launch checklist for SaaS apps built quickly with AI coding tools. It focuses on mistakes that look fine in a demo but become risky in production: missing server auth, weak tenant isolation, exposed secrets, unverified payments and expensive public endpoints.
Yes. Clear textual content, internal links, canonical metadata and matching structured data make it easier for search engines and answer engines to understand and cite the page.
No. GoForLaunch catches repeatable launch risks and explains fixes. Context-heavy architecture decisions still need human review, especially before regulated or enterprise deployments.